The proposed Resource (Neuroimaging Analysis Center or NAC) is a computer science-based, application oriented image processing laboratory that is solidly established in a rich clinical environment. The proposal represents a continuation and expansion of our ongoing efforts in the algorithmic domain, in basic and clinical applications. We propose to expand our high performance computing facility, focusing on neuroimaging applications in the form of collaborative projects as well as providing training and educational support for the local, national and internal scientific community. We plan to disseminate the scientific and clinical tools developed within the NAC and make it available for a wide range of application within and outside of the field of clinical neurosciences and neurosurgery. The main focus of the NAC is to develop post-processing methods for digital medical imaging data and to use these algorithms for clinical applications. The ultimate goal of the work conducted in the NAC is to have fully automated identification of relevant structures from the images for quantitative morphologic analysis of the brain and for visualization of these structures to be applied to: (1) interactive visualization during neurosurgery; (2) the identification and follow-up of white matter lesions in multiple sclerosis (MS); (3) the identification, quantification, visualization and follow-up of morphometric anomalies in Alzheimer's disease, (4) the identification, quantification, visualization and follow- up of morphometric anomalies in Schizophrenia. Three basic algorithmic approaches (segmentation, registration and visualization) are the Core Technologies which will be advanced by the scientists of the Resource. The continuously expanding and improving interactive digital brain atlas will serve as a basis for many of the algorithms and applications, as well as for teaching purposes. These Core Technologies will be utilized for all Collaborative and Service Projects. The existing and continuously upgraded High Performance Computing (HPC) facilities of the Center are equally important as in infrastructure hardware resource. Algorithms that are used extensively in the day-to-day operation of the NAC will be ported into state of the art cluster facilities. This will significantly speed up the execution of algorithms and will improve availability and utilization of the resources. In the context of this proposal the presented primary applications of the technology to schizophrenia, multiple sclerosis, Alzheimer's disease and image guidance in neurosurgery will be the major foci for three basic approaches to the extraction of information from images: quantitative manual, quantitative automated, and qualitative. These fundamental methods will also be utilized in the planning and simulation of neurosurgical procedures, many of which ultimately take place in the operating room or within an open-MRI system. These major efforts along with and other, smaller, projects represent the foundation of the proposed NAC which will focus, expand and enhanced the existing resources available for a wide range of applications. The NAC will provide a vehicle to the dissemination of the results of our research to a larger user community.